Instructions to use WaveMatrix/PaddleOCR-VL-1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WaveMatrix/PaddleOCR-VL-1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="WaveMatrix/PaddleOCR-VL-1.5")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WaveMatrix/PaddleOCR-VL-1.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use WaveMatrix/PaddleOCR-VL-1.5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WaveMatrix/PaddleOCR-VL-1.5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/WaveMatrix/PaddleOCR-VL-1.5
- SGLang
How to use WaveMatrix/PaddleOCR-VL-1.5 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "WaveMatrix/PaddleOCR-VL-1.5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "WaveMatrix/PaddleOCR-VL-1.5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use WaveMatrix/PaddleOCR-VL-1.5 with Docker Model Runner:
docker model run hf.co/WaveMatrix/PaddleOCR-VL-1.5
File size: 2,059 Bytes
60ba429 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | {
"architectures": [
"PaddleOCRVLForConditionalGeneration"
],
"attention_probs_dropout_prob": 0.0,
"auto_map": {
"AutoConfig": "configuration_paddleocr_vl.PaddleOCRVLConfig",
"AutoModel": "modeling_paddleocr_vl.PaddleOCRVLForConditionalGeneration",
"AutoModelForCausalLM": "modeling_paddleocr_vl.PaddleOCRVLForConditionalGeneration"
},
"compression_ratio": 1.0,
"head_dim": 128,
"hidden_act": "silu",
"hidden_dropout_prob": 0.0,
"hidden_size": 1024,
"ignored_index": -100,
"image_token_id": 100295,
"intermediate_size": 3072,
"max_position_embeddings": 131072,
"max_sequence_length": null,
"model_type": "paddleocr_vl",
"num_attention_heads": 16,
"num_hidden_layers": 18,
"num_key_value_heads": 2,
"pad_token_id": 0,
"rms_norm_eps": 1e-05,
"rope_scaling": {
"mrope_section": [
16,
24,
24
],
"rope_type": "default",
"type": "default"
},
"rope_theta": 500000,
"sliding_window": null,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.55.0",
"use_bias": false,
"use_cache": false,
"use_flash_attention": false,
"video_token_id": 101307,
"vision_config": {
"architectures": [
"PaddleOCRVisionModel"
],
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_paddleocr_vl.PaddleOCRVLConfig",
"AutoModel": "modeling_paddleocr_vl.PaddleOCRVisionModel"
},
"hidden_act": "gelu_pytorch_tanh",
"hidden_size": 1152,
"image_size": 384,
"intermediate_size": 4304,
"layer_norm_eps": 1e-06,
"model_type": "paddleocr_vl",
"num_attention_heads": 16,
"num_channels": 3,
"num_hidden_layers": 27,
"pad_token_id": 0,
"patch_size": 14,
"spatial_merge_size": 2,
"temporal_patch_size": 2,
"tokens_per_second": 2,
"torch_dtype": "bfloat16"
},
"vision_start_token_id": 101305,
"vision_end_token_id": 101306,
"vocab_size": 103424,
"weight_share_add_bias": true,
"use_3d_rope": true,
"rope_is_neox_style": true
}
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